AI research
Applied research on agents, LLMs, and world models — how they reason, how they fail, and how to make them reliable in real work.
Herald Labs does applied AI research on agents and turns what we learn into products — figuring out how humans and AI agents will actually work together.
Applied research on how models reason, how they fail, and how to make them reliable in real work.
Every line of research ends in something you can use — an application, a tool, a system.
Herald Labs doesn't publish papers and stop there. Every line of research ends in something you can use — an application, a tool, a working system.
Applied research on agents, LLMs, and world models — how they reason, how they fail, and how to make them reliable in real work.
Very cool applications built around agents — products where an agent isn't a demo, it's the engine doing the actual work.
New interfaces, workflows, and operating patterns for teams made of humans and agents working side by side.
From frontier LLMs and world models down to the scaffolding, evaluation, and tooling that make raw capability dependable.
Lessons from agent operations, evaluation, and QA — published so the next person or agent can build on them.
The future of work has agents in it. Our job is to work out what that actually looks like — and build it, one working system at a time.
Each project is small enough to ship, concrete enough to test, and documented well enough for the next person or agent to continue without folklore.
Start with a real question about how agents and humans work — not a technology looking for a use case.
Humans and AI agents build the smallest end-to-end version that can be honestly judged.
Run it on real work, real documents, real users. If it only works in a showroom, it doesn't work.
Release the product, publish the lesson, keep the receipts — then scale it or kill it.
If you're working on agents, want to build with us, or have a hard problem that needs one — we want to hear from you.